Field
Exemplary embodiments of the present invention relate to a method and apparatus for improving speed of fingerprint registration and authentication, and more particularly, to a method for setting a predetermined region including each pixel configuring a fingerprint image in its center, modifying the fingerprint image by calculating an average value of shading values of pixels in the predetermined region, and selecting a feature point in the modified image.
Discussion of the Background
Since a pattern of a fingerprint is different from individual to individual, fingerprints are mainly being applied to the personal identification field. Particularly, fingerprints are widely being used in various fields such as finance, criminal investigation, security, or the like.
A fingerprint sensor has been developed to identify a person by recognizing his or her fingerprint. The fingerprint sensor is a device for recognizing a fingerprint when a finger of a person touches the fingerprint sensor, and is being used as a means for determining whether a user is valid.
In methods for implementing a fingerprint recognition sensor, there are various well-known methods such as an optical method, a heat detection method, a capacitive method, etc. Among them, a fingerprint recognition sensor of the capacitive method obtains a shape of a fingerprint (a fingerprint pattern) by detecting a change of a capacitance according to a shape of peaks and valleys of the fingerprint when a surface of a finger of a person touches a conductive sensing pattern.
Recently, a mobile device is providing not only a communication function, such as a phone and message transmission service, but also various additional functions in which personal information is utilized for finance, security, etc., and the importance of a need for a locking device of the mobile device has emerged. In order to improve a locking effect of the mobile device, a terminal in which a locking device using fingerprint recognition is installed is being earnestly developed.
FIGS. 1(A) and 1(B) illustrate one example in which a fingerprint sensor is installed in a mobile device, for example, a smart phone.
First, referring to FIG. 1(A), a smart phone 10 includes a display 11 having a function of an input unit in a touch screen method, and a fingerprint sensor 12 is installed below the display 11. The fingerprint sensor 12 is formed in a lower region of a body of the smart phone 10 and is implemented with a home key which moves a screen of the display 11 to a home.
Next, a smart phone 20 shown in FIG. 1(B) also includes a fingerprint sensor 22 installed with a home key below a display 21. A size of the fingerprint sensor shown in FIG. 1(B) is formed to be smaller than that of the fingerprint sensor shown in FIG. 1(A).
Fingerprint detection methods are largely classified as a touch method (or, an area method) and a swipe method, and the touch method is generally applied to the fingerprint sensor 12 shown in FIG. 1(A) and the swipe method is generally applied to the fingerprint sensor 22 shown in FIG. 1(B).
The touch method is a method for obtaining a fingerprint image in a corresponding fingerprint sensing area when a finger is put on the fingerprint sensor 12 for a predetermined time. Meanwhile, the swipe method is a method for obtaining a complete fingerprint image by combining fragmentary fingerprint images as a single image after reading the fragmentary fingerprint images by the fingerprint sensor 22 sensing a fingerprint moving on the fingerprint sensor 22 when a finger moves on the fingerprint sensor 22 in a sliding manner.
When a fingerprint image is obtained with the above methods, the obtained fingerprint image and a previously registered fingerprint image are compared, whether the two fingerprint images match is determined, and fingerprint authentication is performed according to the determination result. As such, in order to determine whether the two fingerprint images match, points which are features in each of the fingerprint images are extracted, and a comparison of the feature points should be performed.
Accordingly, various algorithms for extracting points which are features in fingerprint images have been developed and improved, and thus accuracy of fingerprint authentication is increasing.
However, in order to increase the accuracy of fingerprint authentication, an amount of computation performed to extract points which are features in a fingerprint image increases, and thus there is a disadvantage in that a time used for fingerprint authentication is increased.
Recently, a need for an algorithm for increasing the accuracy of fingerprint authentication and also performing the fingerprint authentication in a limited time using only limited hardware resources is increasing.